The NYUCI Genomics Facility constitutes the Microarray Unit of the NYU Genome Technology Core and it coordinates its microarray informatics efforts with the Center for Health Informatics and Bioinformatics (CHIBI) to process and analyze a large majority of array-based data generated in our laboratory. Microarray-centered informatics is primarily applied to two high-capacity profiling areas:

1. genome-wide microarray gene expression profiling
2. array-based Q-PCR microRNA expression profiling

We provide fee-for-service assistance with the following modules of typical experimental workflows:

Study and Experiment Design (FREE) - in-depth discussion of the biological context and key questions asked; experiment type selection (pair-wise comparison, time series, multiparametric studies); best cost-effective strategies for replicate studies; optimization of experimental conduct to identify and minimize sources of experimental noise; sample preparation strategy and array platform selection.

Data Preprocessing and Management - upload of annotated raw data into institutional repository and into client analysis environments; data normalization and transformation (probe-level summarization principles (Affymetrix), condition-centered normalization strategies, experiment interpretation options); data-filtering (intensities, QC metrics such as Ct values and Q-PCR flags (microRNA)); data-reduction strategies.

Differential Expression - statistical significance (t-test statistics, one-way and two-factor ANOVA, multiple testing corrections, Significance Analysis of Microrarrays, non-parametric tests, Bayesian estimation of temporal regulation)

Pattern Matching - ad hoc and post hoc template-matching procedures to establish non-overlapping patterns of gene expression.

Clustering of Reduced-size Data - unsupervised (hierarchical), semi-supervised (K-means clustering, Self-Organizing Maps), resampling for support.

Classification - strategies to classify biological samples and predicting outcomes based on gene expression profiles (Support Vector Machines, Discriminant Analysis Classifiers, K-nearest neighbor).

MicroRNA mRNA Target Prediction - cross-validation of target prediction algorithms; correlation of miRNA profiles with mRNA and protein expression patterns derived from gene expression and proteomics data; context-score ranking of target mRNAs; determination of patterns of post-transcriptional control (microRNA:mRNA regulatory networks).

Biological Significance - in-depth data and literature mining; functional annotation of gene groups and determination of context-specific biological meaning of expression profiling results using integrated biological knowledgebases (e.g. NIH DAVID database for annotation, visualization and integrated discovery, GSE - gene set enrichment analysis, etc.).

Integration of Multiple Species Data - batch translation of standard IDs into orthologous lists; matching of expression patterns from patient and model organism samples.

Data Publication - formatting data for upload to public repositories (NCBI GEO); visualization of data for publication purposes; generating specific-focus figures and tables for grant applications, research articles and scientific conference presentations.

GENESPRING GX10 AVAILABLE FOR MICROARRAY ANALYSIS BY USERS

The Agilent Genespring GX10 version can be downloaded from the Agilent web site (as a free trial version), and once installed locally and started up, it will ask for these credentials to become fully functional:

Host: 10.147.55.37
Port: 8080
Username/Password (must be requested by email from Genomics)

We recommend installing Genespring GX on a PC as there have been occasional unresolved issues with Macs.

IMPORTANT:
A common floating Genespring license is available for the entire campus, allowing one user access at a time, so it is crucial that users reserve analysis time and close the program in a timely manner. We use the Skirball reservation system located here (works with Kerberos ID and corresponding password, and you must first be authorized to use it - send an e-mail with your Kerberos ID to request authorization):

Please adhere to this sign-up system stringently and try to book only reasonable amounts of time per day (3 hours maximum suggested), as we expect a growing user base for the program.

There is a dedicated PC for Genespring analysis in Rusk 809 that users are welcome to use after signing up for the time here (as above, the sign-up works with Kerberos ID and corresponding password, and you must first be authorized to use it - send an e-mail with your Kerberos ID to request authorization).

If you have issues with the program installation and/or performance, please contact Jiri Zavadil or Steve Sotero. For detailed questions related to the use of the program for analysis, call Agilent GeneSpring Support. (+1-800-227-9770, Option 3, Option 5, Option 2)